Both obesity (Body Mass Index (BMI)e30) and prostate cancer (PCa) constitute significant public health problems, for which there are persistent disparities between African American men (AAM) and Non-Hispanic European men (EAM). Obesity as a physiological state is characterized by significant alterations in the individual's hormonal profile. Since PCa is a hormonal disease, it appears biologically plausible that obesity affects PCa risk, possibly through the altered tumor growth enabled by the hormonal imbalances. This effect may be even more pronounced in AAM since their PCa tumors tend to demonstrate more aggressive biological behavior at baseline. Indeed, a few studies have linked obesity to more aggressive PCa in AAM specifically, suggesting involvement of obesity in PCa disparity. However, to date, the mechanistic biology studies aimed to elucidate the effects of obesity on PCa risk in AAM and EAM are lacking. In concordance with the published literature, our recent preliminary data suggest that obesity may be a PCa risk factor in AAM, and the extent of risk is determined by the individual's genetic variation. The goal of our project is to understand the joint impact of germline genetic variations and obesity on prostate tumor biology and PCa risk in AAM and EAM. We hypothesize that select genetic variation, when combined with the environment of obesity, influences PCa risk by impacting key cellular processes relevant to the tumor biology. To test this hypothesis, a functional integrated approach is proposed, that utilizes prostate tumor biology as a starting point. In the Aim 1, we will investigate whether there are differences in the gene expression profiles in prostate tumors and healthy prostate tissue of obese and non-obese men in each race. In the Aim 2, we will test the functional significance of the identified genes. Finally, in te Aim 3 we propose to link obtained data to PCa risk through variation in the germline genome. Significance. Understanding the specific role of obesity in PCa risk is crucial for efficient development of individualized PCa risk estimation in AAM and EAM; selection of the most appropriate treatment modalities; estimating the risk of progression; advancing knowledge of the tumor biology in AAM and EAM; and developing targeted risk reduction interventions. Innovation. Our work is innovative, comprehensive and contemporary in that we propose functionally relevant genetic variation to be incorporated in the risk prediction. Future direction. Guided by our findings, we plan to launch a clinical preventive study aimed to validate the results in a larger cohort of AAM and EAM, improve the proposed approach, and test the chemopreventive and/or lifestyle interventions targeted towards specific tumor and genetic features in AAM and EAM. In addition, our proposed model can be applied to study gene-environmental interactions in virtually any other malignancy.